Fast Artificial Neural Network Library 2.1.0b C/C++ script

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    Specification

  • Version: 2.1.0b
  • File size: 0 KB
  • File name: fann-2.1.0beta.zip?download
  • Last update:
  • Platform: Windows / Linux / Mac OS / BSD / Solaris
  • Language: C/C++
  • Price:LGPL
  • Company: Steffen Nissen (View more)

Fast Artificial Neural Network Library 2.1.0b script description:



Fast Artificial Neural Network Library 2.1.0b is a C/C++ script for Earth Sciences scripts design by Steffen Nissen. It runs on following operating system: Windows / Linux / Mac OS / BSD / Solaris.
Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C.

Publisher review:
Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C. Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported.It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. PHP, C , .NET, Ada, Python, Delphi, Octave, Ruby, Pure Data and Mathematica bindings are available. A reference manual accompanies the library with examples and recommendations on how to use the library. A graphical user interface is also available for the library. Features: - Multilayer Artificial Neural Network Library in C - Backpropagation training (RPROP, Quickprop, Batch, Incremental) - Evolving topology training which dynamically builds and trains the ANN (Cascade2) - Easy to use (create, train and run an ANN with just three function calls) - Fast (up to 150 times faster execution than other libraries) - Versatile (possible to adjust many parameters and features on-the-fly) - Cross-platform (configure script for linux and unix, dll files for windows, project files for MSVC and Borland compilers are also reported to work) - Several different activation functions implemented (including stepwise linear functions for that extra bit of speed) - Easy to save and load entire ANNs - Can use both floating point and fixed point numbers (actually both float, double and int are available) - Cache optimized (for that extra bit of speed) - Framework for easy handling of training data sets - Graphical Interface - C Bindings - PERL Bindings - PHP Extension - Python Bindings - Delphi Bindings - .NET Bindings - Mathematica Extension - Octave Extension - Squeak Smalltalk bindings
Operating system:
Windows / Linux / Mac OS / BSD / Solaris

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Fast Artificial Neural Network Library
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